207 research outputs found

    Psychophysics of Artificial Neural Networks Questions Classical Hue Cancellation Experiments

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    We show that classical hue cancellation experiments lead to human-like opponent curves even if the task is done by trivial (identity) artificial networks. Specifically, human-like opponent spectral sensitivities always emerge in artificial networks as long as (i) the retina converts the input radiation into any tristimulus-like representation, and (ii) the post-retinal network solves the standard hue cancellation task, e.g. the network looks for the weights of the cancelling lights so that every monochromatic stimulus plus the weighted cancelling lights match a grey reference in the (arbitrary) color representation used by the network. In fact, the specific cancellation lights (and not the network architecture) are key to obtain human-like curves: results show that the classical choice of the lights is the one that leads to the best (more human-like) result, and any other choices lead to progressively different spectral sensitivities. We show this in two ways: through artificial psychophysics using a range of networks with different architectures and a range of cancellation lights, and through a change-of-basis theoretical analogy of the experiments. This suggests that the opponent curves of the classical experiment are just a by-product of the front-end photoreceptors and of a very specific experimental choice but they do not inform about the downstream color representation. In fact, the architecture of the post-retinal network (signal recombination or internal color space) seems irrelevant for the emergence of the curves in the classical experiment. This result in artificial networks questions the conventional interpretation of the classical result in humans by Jameson and Hurvich.Comment: 17 pages, 7 figure

    Highly Conductive Carbon Fiber Reinforced Concrete for Icing Prevention and Curing

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    This paper aims to study the feasibility of highly conductive carbon fiber reinforced concrete (CFRC) as a self-heating material for ice formation prevention and curing in pavements. Tests were carried out in lab ambient conditions at different fixed voltages and then introduced in a freezer at −15 °C. The specimens inside the freezer were exposed to different fixed voltages when reaching +5 °C for prevention of icing and when reaching the temperature inside the freezer, i.e., −15 °C, for curing of icing. Results show that this concrete could act as a heating element in pavements with risk of ice formation, consuming a reasonable amount of energy for both anti-icing (prevention) and deicing (curing), which could turn into an environmentally friendly and cost-effective deicing method.Authors want to acknowledge Generalitat Valenciana (PROMETEO/2013/035) for their economic support on this research, including funds for covering the costs to publish in open access
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